PENGENALAN MOTIF BATIK MENGGUNAKAN ROTATED WAVELET FILTERDAN NEURAL NETWORK

Authors

  • Bernardinus Arisandi
  • Nanik Suciati
  • Arya Yudhi Wijaya
Views: 935 Downloads: 793

DOI:

https://doi.org/10.12962/j24068535.v9i2.a34

Abstract

Batik merupakan kriya tekstil yang menjadi kekayaan intelektualbangsa Indonesia dan telah diakui oleh UNESCO sejak tanggal 2 Oktober 2009. Namun demikian, masyarakat Indonesia sendiri belum banyak yang mengetahui tentang perkembangan dan jenis batik yangmerupakan kekayaan budaya tersebut. Pada penelitian ini, dikembangkan sebuah perangkat lunak pengenalan motif batik yang dapat digunakan untuk mengenali motif batik secara otomatis. Fitur tekstur dari citra batik diekstrak menggunakan Rotated Wavelet Transform. Selanjutnya, hasil ekstraksi berupa vektor fitur diklasifikasikan ke dalam motif-motif batik menggunakan metode klasifikasi Neural Network (NN). Uji coba menggunakan dataset testing sama dengan dataset training menghasilkan akurasi tertinggi 100%. Sedangkan uji coba menggunakan dataset testing yang berbeda dengan dataset training menghasilkan akurasi tertinggi 78,26%. Kedua nilai akurasi tersebut didapat pada learning rate 0.8, momentum 0.9, jumlah komposisi node hidden layer [40 10 1], dan level dekomposisi ke-5.

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Published

2011-07-01

Issue

Vol 9, No 2, Juli 2011

Section

Articles

How to Cite

[1]
B. Arisandi, N. Suciati, and A. Y. Wijaya, “PENGENALAN MOTIF BATIK MENGGUNAKAN ROTATED WAVELET FILTERDAN NEURAL NETWORK”, JUTI, vol. 9, no. 2, pp. 15–21, Jul. 2011, doi: 10.12962/j24068535.v9i2.a34.

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